Pawel M Chilinski

Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages

Factorial Hidden Markov Models (FHMMs) are powerful models for sequential data but they do not scale well with long sequences. We propose a scalable inference and learning algorithm for FHMMs that draws on ideas from the stochastic variational inference, neural network and copula literatures. Unlike…